Denoising Textures is a Different Ballgame Altogether!
The human brain effortlessly deciphers colors and textures from visual stimuli and reconstructs the world around us, yet preserving such details remains challenging in image denoising. While significant progress has been made in generic image denoising, the problem of texture denoising has remained relatively under-explored. Fine details, such as intricate patterns and repetitive structures, often suffer from over-smoothing even in deep learning based approaches for denoising. In this paper, we analyze the behavior of state-of-the-art (SOTA) denoisers on texture datasets and show that performance improvements are possible only by fine-tuning the denoisers on the texture datasets. Surprisi...
| Authors | Saptarshi Mandal, Oindrila Haldar, Chirayata Bhattacharya et al. |
|---|---|
| Primary category | eess.IV |
| Published | 15 October 2026 |
| Last updated at source | 15 October 2026 |
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